National Academies Press: OpenBook

Mapping the Zone: Improving Flood Map Accuracy (2009)

Chapter: 5 Coastal Flooding

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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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Suggested Citation:"5 Coastal Flooding." National Research Council. 2009. Mapping the Zone: Improving Flood Map Accuracy. Washington, DC: The National Academies Press. doi: 10.17226/12573.
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5 Coastal Flooding A primary objective of coastal flood studies is coastal flood mapping evolved significantly following to predict the extent and force of floodwaters hurricanes Katrina and Rita in 2005, and during the over land. Because of sparse empirical records Map Modernization Program FEMA was expanding and the statistical rarity of extreme coastal events, and significantly modifying its guidance documents on coastal flood prediction relies on complex numerical coastal flood mapping. The end result is that coastal models that approximate the processes and ­phenomena flood mapping is much more complex and uncertain that lead to coastal floods. The predictions yield base than riverine flood mapping, and its accuracy is less flood elevations (BFEs) and spatial areas of flood haz- able to be characterized quantitatively. Accordingly, ard, which are presented on the Federal Emergency this chapter presents a survey of coastal flood mapping Management Agency’s (FEMA’s) coastal flood maps. methodologies and the committee’s assessment of the This chapter reviews the methodology of coastal flood effectiveness of alternative approaches. mapping. The focus is on hurricane-induced flooding, which is responsible for all the major aspects of coastal FLOOD HAZARDS IN COASTAL SYSTEMS flooding, including storm surge, heavy rain, and over- flowing rivers. Coastal flood hazards arise from wave and surge The committee did not undertake a set of detailed dynamics that originate in the ocean and subsequently case studies of coastal flood mapping, nor is it possible interact with bathymetric and topographic features on to obtain lower bound estimates of flood map accuracy the ocean bottom and land surface (Figure 5.1), respec- by analysis of stage height records as was done for tively. Coastal flood models must account for these riverine flooding (Chapter 4). Coastal flood mapping features throughout the coastal zone as well as processes differs from inland flood mapping in several ways. associated with the storm surge and waves that create First, there is much greater dependence on simulation the flood hazard (FEMA, 2006b). ­ Bathymetry and models in coastal mapping along with less ability to topography change constantly as a result of storms and make inferences from historical gage records as for erosion, and also vary geographically. These geographic inland mapping. In riverine flooding, the floodwaters differences affect BFEs and result in different coastal flow down the river system past a succession of stream flooding responses and flood hazard areas. For example, gages so the maximum discharge and water surface the Pacific coast is characterized by steep bathymetry elevation are recorded at many locations. In coastal and narrow coastal shelves, and flooding is dominated flooding, the storm comes onshore in a direction trans- by waves rushing up the shore (wave runup). In con- verse to the line of tide gages along the coast. Indeed, trast, the Atlantic and Gulf coasts are characterized by no tide gage may be located at the point of maximum wide, shallow coastal shelves, and flooding is dominated effect of a coastal storm. Second, the methodology for by storm surge and breaking waves. Erosion continually 67

68 MAPPING THE ZONE V Zone A Zone Wave Height Greater Than 3 Ft. Wave Height Less Than 3 Ft. Base Flood Elevation Including Wave Effects 100-Year Stillwater Elevation Shoreline Sand Beach Buildings Overland Vegetated Region Limit of Flooding Wind Fetch and Waves FIGURE 5.1  Onshore features that affect the propagation of waves, flood insurance rate zones (V and A zones), and base flood elevations. The 100-year stillwater elevation is the water level with a 1 percent annual chance of being exceeded in a given year. SOURCE: FEMA (2003). figure 5-1 revised or episodically changes the ground surface and com- level). All of these factors are included in coastal flood plicates flood hazard mapping, especially along the models to estimate the BFE. Atlantic coast, which has dunes that are reshaped by storms, and, to a lesser degree, the Gulf coast. FEMA COASTAL FLOOD MODELING Storm surge, tides, and waves are the greatest METHODOLOGY contributors to coastal flooding. Storm surge is the pulse of water that washes onto shore during a storm, The Basic Structure of Current Coastal measured as the difference between the height of the Flood Models storm tide and the predicted astronomical tide. It is driven by wind and the inverse barometric effect of low Coastal flood models estimate BFEs using empiri- atmospheric pressure, and is influenced by tides and by cal and probabilistic input data and two modeling steps uneven bathymetric and topographic surfaces. Faster (Figure 5.3 and Table 5.1): wind speeds and larger storms create a greater storm surge potential. Storm surge alters topographic features 1. ��������������������������������������������� Storm surge models are often loosely coupled that might otherwise dampen the effects of surge and with wave models to calculate the 1 percent annual wave forces. For example, sand dunes that normally chance stillwater elevation (SWEL) and the wave prevent storm water progress onto a barrier island may dynamics associated with a coastal flooding event. be reshaped or even removed during a severe storm. Recent flood studies in Mississippi and Louisiana used Water surface elevations at the shoreline are a loosely coupled two-dimensional (2-D) surge and wave combination of the average water level determined by models to calculate the SWEL and wave setup. wind setup (due to the direct action of wind stresses at 2. �������������������������������������������� The SWEL value (with or without wave setup) the air-sea interface) and wave setup (due to breaking from the wave and surge models is used to calculate waves, Figure 5.2) and a fluctuating water level caused wave crest values using erosion and wave calculations by wave runup (the maximum extent of high-velocity through the Coastal Hazards Analysis and Modeling uprush of individual waves above the average water Program (CHAMP) and the Wave Height Analysis

COASTAL FLOODING 69 R(t) H <η> SWL β FIGURE 5.2  Schematic of wave setup (η; rise in the water surface caused by breaking waves of height H) and wave runup (R(t); the rush of wave water up a slope or structure). Wave setup and wave runup raise water elevations above the stillwater level (SWL). SOURCE: U.S. Geological Survey, <http://coastal.er.usgs.gov/hurricanes/impact-scale/water-level.html#runup>. for Flood Insurance Studies (WHAFIS) program. The Figure 5-2 revised lations of wave height and runup in flood map projects recent Mississippi study used the SWEL and wave setup for Atlantic and Gulf coast communities. The NRC calculated by the Advanced Circulation (ADCIRC) (1977) concluded that wave height predictions should and Simulating WAves Nearshore (SWAN) models to be included in coastal flood mapping and provided calculate the wave crest in CHAMP. The wave crest a methodology to account for varying fetch lengths is combined with the SWEL and wave setup to yield (length of water over which a given wind has blown), the BFE. Depending on the region, wave runup and barriers to wave transmission, and regeneration of overtopping may have to be calculated and added to the waves likely to occur over flooded land areas. Based on wave crest. the NRC (1977) recommendations, FEMA developed WHAFIS to provide wave heights for the BFEs. Evolution of Coastal Flood Models and Mapping FEMA has also made many incremental improve- ments in probabilistic methods for selecting an ensem- Prior to 1975, coastal BFEs for Flood Insurance ble of hurricane and storm parameters and return Rate Maps (FIRMs) were calculated using limited periods; storm surge modeling; and calculation of historical records and an early storm surge model, wave setup, wave runup, wave crest, erosion, and the but without consideration of waves. In the late 1970s, effects of structures on surge and waves. For example, FEMA supported the development of a 2-D storm the Joint Probability Method ( JPM), introduced in surge model (FEMASURGE) for calculating the 1981, was used to determine the hurricane ensemble SWEL caused by storm surge, again without consider- and return period in coastal regions based on available ation of wave effects on the storm surge or BFEs. These hurricane data and statistical properties of hurricane early models used simplified assumptions, coarse grid wind parameters at landfall. The catastrophic flood- resolutions, and a simple parametric hurricane model ing in Louisiana and Mississippi during Hurricane to minimize computational effort. Katrina in 2005 triggered new interest in developing In 1977, FEMA asked the National Research more advanced models. JPM has been improved, and Council (NRC) to determine how to incorporate calcu- the Interagency Performance Evaluation Task Force

70 MAPPING THE ZONE Probabilistic Hurricane Hurricane ensemble and hurricane wind data return period model Topographic Bathymetric Existing and probabilistic data data input data 2-D storm surge 2-D wave model model Coupled surge and wave 1 percent annual chance SWEL (including wave setup) Wave model for at SWEL shore Wave crest CHAMP/WHAFIS and BFE erosion and wave calculations calculation along I-D transects Wave crest and 1 percent annual chance post-storm BFE and wave crest topography Flood insurance FIRM rate zones FIGURE 5.3  Current FEMA coastal mapping procedures used in Mississippi and Louisiana. In these studies, two-dimensional surge Figure 5-3.eps (ADCIRC) and wave (SWAN for Mississippi and STeady State spectral wave [STWAVE] for Louisiana) models are used to calculate the 1 percent annual chance stillwater elevation, and CHAMP/WHAFIS is used to calculate overland wave crest and post-storm topography. The 1 percent annual chance SWEL and the wave crest are then combined to calculate the BFE. NOTE: FIRM = Flood Insurance Rate Map. TABLE 5.1  Elements of FEMA’s Current Coastal Flood Mapping Process Coupled Surge and Wave Models for Empirical and Probabilistic Input Data SWEL Calculation Wave Crest and BFE Calculation • Hurricane data • 2-D storm surge model • CHAMP/WHAFIS erosion and wave calculations along • Probabilistic hurricane wind model data • 2-D wave model one-dimensional (1-D) transects • Hurricane ensemble and return period data • Post-storm topographic data to verify CHAMP/WHAFIS • Bathymetric data results • Pre- and post-storm topographic data

COASTAL FLOODING 71 (IPET, 2008) developed the JPM-OS (Optimal Sam- results are then interpolated to produce the wave crest pling) method to reduce the number of hurricanes in over a 2-D onshore environment. the hurricane ensemble. The Empirical Simulation Wave crests calculated by CHAMP/WHAFIS Technique (EST), was developed to reduce the compu- have not been sufficiently validated, creating potentially tational burden by considering only the combinations significant uncertainties in BFE estimates. Factors that of storm characteristics that have been observed in the contribute to the uncertainty of WHAFIS wave crest historical record. A comparison of the JPM and EST calculations include the following (Sheng and Alymov, methods appears in Divoky and Resio (2008). A new 2002): generation of storm surge and wave models is now being used for flood mapping in Mississippi, Louisiana, • Wave transformation is a 2-D process that can- Texas, and North Carolina and will be used in other not be represented in a 1-D model. states in the future. • WHAFIS wave crests and BFEs are not 1 percent FEMA’s guidelines for coastal flood mapping have annual chance values (i.e., probabilistic wave conditions also evolved. Policies and procedures were established are not incorporated in the WHAFIS calculations). for storm surge modeling by 1985 and for wave and V • Surge and wave are completely decoupled, which zone modeling by 1995. Updates in coastal modeling may lead to over- or underestimates of the BFE. guidance accelerated in 2002. Separate guidance has • The 540-square-foot rule for dune erosion (i.e., been developed for the Atlantic and Gulf coasts, the a dune exceeding a cross-sectional area of 540 square Pacific coast, and sheltered coastlines. Yet even with feet will not be breached in a 1 percent annual chance these updates, the recent switch to coupled storm storm) has not been validated. surge-wave modeling for flood map production is still • The approach for wave dissipation by vegetation, “beyond the scope of these guidelines” (FEMA, 2007a), buildings, and levees has not been validated. and mapping contractors are referred to the specific • One-dimensional transects do not reflect 2-D user’s manual for each model. FEMA is currently work- terrain. ing with individual mapping contractors to implement • Manual interpolation of 1-D results to two the models in flood map production. dimensions is subjective. Wave Height Analysis for Flood Insurance Studies Despite these known limitations, WHAFIS has (WHAFIS) been the wave analysis method recommended by FEMA since 1989. A number of 2-D models have been WHAFIS analyzes wave effects along one- developed, and studies demonstrate that coupled 2-D d ­ imensional (1-D) transects normal to the shore models are at least as accurate as WHAFIS and in most (Figure 5.4) to determine the wave height. The rela- cases are better at representing the fullness of wind tively simple 1-D method was originally recommended wave crest and storm surge dynamics in coastal flood because wave transformation processes in shallow water zones (e.g., Sheng and Alymov, 2002). The current were not well understood, and robust 2-D wave models 2-D coupled surge and wave models use probabilistic and the computational power to run them did not exist methods, whereas WHAFIS determines wave crest (NRC, 1977). Patches added to the original WHAFIS elevation on top of the SWEL along 1-D transects. program since 1989 include methods to calculate wave Which modeling approach yields more uncertainty in height elevations above the storm surge elevation the BFE value has not been studied. and wave setup along 1-D transects. The improved WHAFIS was combined with patches for calculating FEMA Coastal Flood Modeling in the wave runup and storm-induced dune erosion along 1-D Post-Katrina Era transects into a new software package, CHAMP. The Since Hurricane Katrina in 2005, FEMA has encouraged rapid advancements in coastal flood model- See description and references at <http://www.fema.gov/plan/ ing and mapping. Improvements currently under way prevent/fhm/dl_vzn.shtm#1>.

72 MAPPING THE ZONE FIGURE 5.4  Aerial photograph of the coast near Biloxi, Mississippi, showing the layout of one-dimensional WHAFIS transects (red lines). SOURCE: Courtesy of David Divoky, HSMM/AECOM. Used with permission. Figure 5-4.eps bitmap image include development of better hurricane ensemble In Louisiana, Mississippi, and North Carolina, parameters, more accurate estimates of the return novel approaches to coastal flood mapping are either period of storms in several coastal regions, more accu- under way or have recently been completed. These rate simulations of storms surge and estimations of new coastal mapping studies are the first to replace SWEL in Louisiana and Mississippi, and increased FEMASURGE with the ADCIRC model and could use of very fine, unstructured grids (100 meters or less) be used as part of a more comprehensive assessment to resolve complex coastal terrains and enable the use of methods for enhancing mapping—for example, by of high-resolution lidar (light detection and ranging) gathering more data for verifying wind, storm surge, data. and wave models (see below). FEMA (2006b) recommended merging develop- ments in hydrodynamic and statistical methods with FROM MODELS TO MAPS: DEVELOPING established methods for wave analysis, erosion assess- THE NEXT GENERATION OF COASTAL ment, and flood hazard mapping. However, coupled FLOOD MODELS 2-D surge and wave models are not yet fully integrated into mapping practice because 2-D wave models “do Coastal flood models—and by extension, coastal not incorporate bottom friction and obstruction effects flood maps—will continue to be improved in the of the sort considered by WHAFIS” and FEMA has coming decades, driven by the increased availability not developed guidelines for 2-D overland wave mod- of high-resolution topographic data and more sophis- eling (FEMA, 2008b). Recent applications of coupled ticated models. This section identifies opportunities 2-D surge and wave models have demonstrated their to improve the accuracy of coastal flood models and ability to calculate wave setup and wave crest (Sheng recommends ways to guide the development of the next and Alymov, 2002; IPET, 2008). generation of coastal flood models and maps.

COASTAL FLOODING 73 Decreasing Uncertainty in Coastal Flood Models Recommendation. FEMA should work with other federal agencies and academic institutions to develop The BFE is a key variable used to define flood haz- a test bed to assess and compare the various models ard areas on coastal FIRMs. However, it is the final out- used for coastal flood mapping. As a start, FEMA put of the models and reflects uncertainties in the input should compare the flood maps for the New Orleans data and every stage of the modeling process. Major region produced by IPET using coupled 2-D surge sources of uncertainty include calculation of the SWEL and wave models with those produced by FEMA using a 2-D surge model and the non­probabilistic wave using a 2-D surge model and a 1-D wave model. crest using a 1-D WHAFIS model, use of coarse grid resolution and small model domain, use of simple and More Robust 2-D and 3-D Models empirical procedures or models to represent the effect of topographic features on surge and waves, quantification Storm surge has been simulated using 1-D, 2-D, of hurricane return period and ensemble, exaggerated and three-dimensional (3-D) models, although 1-D wind conditions (e.g., 80 miles per hour blowing perpen- models have known shortcomings. After Hurricane dicular to shore), unrealistic wave boundary conditions Katrina, FEMA accelerated the improvement of coastal at the shore, and topographic and bathymetric data. modeling methodology by adopting the more advanced Sources of uncertainty in storm surge and wave models 2-D surge model ADCIRC and the 2-D wave model are shown in Figure 5.5. The impact of uncertainties in SWAN. Although FEMA has not fully embraced the these factors on the accuracy of calculated storm surge use of coupled 2-D surge and wave models to calculate and coastal inundation has not been examined, but may BFEs and wave crests, the successful use of this method need to be quantified to make significant improvements by the Interagency Performance Evaluation Task Force in coastal models and maps. The sensitivity and uncer- increases the likelihood that 2-D methods will eventu- tainty of simulated storm surge and inundation to these ally replace the current 2-D (wave and surge models) factors is beginning to be examined in regional test beds, plus 1-D (WHAFIS/CHAMP) method. such as the one described in Box 5.1. Considerable differences exist among the available Recommendation. FEMA should use coupled 2-D storm surge models in terms of model ­dimensionality, grid surge and wave models to reduce uncertainties asso- resolution, efficiency, and processes modeled. Increasing ciated with the use of a 2-D surge model and the 1-D model grid resolution in the coastal region improves the WHAFIS model. Before choosing which models to model’s ability to resolve local and ­ geometric features incorporate into mapping practice, an analysis of the and increases the accuracy of simulated surge. Increas- impact of various uncertainties on the models should ing the size of the coastal domain enables modelers to be undertaken. simulate hurricane effects further from shore, reducing uncertainty in surge and wave water levels. However, Sometimes even 2-D models cannot represent the both the increased resolution and the increased domain full range of physical processes involved. For example, size add to the computational time of the simulations. marshes, barrier islands, buildings, dunes, and levees Added computational resources enabled recent coastal resist storm surge and waves, and hence can signifi- flood studies in ­Mississippi and Louisiana to use much cantly affect the surge, wave heights, and inundation. higher resolution and larger coastal domains than have These 3-D processes are not adequately resolved in traditionally been used for these types of studies (e.g., FEMA-approved 2-D storm surge models and may IPET, 2008). More efficient surge and wave models require 3-D modeling. Another example concerns would reduce computation costs. flow-structure interaction, which has a significant The accuracy of simulated storm surge and effect on flooding in some regions. Even when the waves is sensitive to the way wave-current interac- SWEL is below the height of a coastal barrier (e.g., a tion is ­ parameterized in the model, including the levee or large dune), the topographic feature may be wave-enhanced drag coefficient, radiation stress, and overtopped and/or eroded. If these processes are not wave-current ­bottom friction. included in the models, flooding and waves in the land

74 MAPPING THE ZONE Dimensionality (1-D, 2-D, 3-D) Schematization Governing equations Domain and grid Model Solution Accuracy algorithm Efficiency Flooding Conservation and drying Inundation dynamics Bed Surge-wave Processes and Resistance Vegetation, dune modeling parameters uncertainties Levee, building Wave-enhanced drag Wave-current interaction Radiation stress Bottom boundary layer Wind and atmospheric pressure Rainfall and river flow Forcing Astronomic tides Open boundary condition Input data (boundary condition) Bathymetry Geometry Topography / ground profile “Structures” / topographic features FIGURE 5.5  Sources of uncertainties associated with storm surge and wave modeling. Although every item in this figure contributes Figure 5-5.eps to the overall uncertainty of the simulated storm surge and waves and the calculated 1 percent annual chance flood elevation, their relative contributions are not well understood because a systematic uncertainty analysis has not been done. area and bays behind the topographic features could be In addition to developing new capabilities, the under­estimated. Hence, it is important to incorporate next generation of coastal flood models can take ­better the effect of topographic features on coastal flood- advantage of the capabilities of existing 2-D and 3-D ing in 2-D or 3-D storm surge and wave models, as models. For example, 2-D wave models already in appropriate. use with storm surge models represent a significant

COASTAL FLOODING 75 BOX 5.1  Coastal Mapping Test Bed Over the last few years, flood mapping along the Atlantic and Gulf coasts has shifted from locally applied storm surge models to the regionally applied ADCIRC model coupled with the SWAN wave model as maps are updated. FEMA has also authorized the use of other storm surge models. These models were typically developed independently from university research efforts. Each model has its own strengths, weaknesses, and data needs. However, there have been little direct comparisons of the models and limited testing to optimize computational efficiency and data needs. An effective way to compare the accuracy and/or efficiency of different models and to optimize the data requirements is to develop a model test bed. One such test bed is being developed under a grant from the National Oceanic and Atmospheric Administration’s (NOAA’s) Integrated Ocean Observing System Program through the Southeast Coastal Ocean Observing Regional Association. The test bed consists of four modeling groups, including the University of Florida (CH3D-SSMS modeling system), the University of North Carolina (ADCIRC model), the University of South Florida (FVCOM), and North Carolina State University (CEMAS based on POM), plus participants from NOAA, FEMA, the U.S. Army Corps of Engineers (USACE), the U.S. Geological Survey, the Florida Department of Emergency Management, the North Carolina Division of Emergency Management, the Northeast Florida Regional Planning Council, Broward County, Florida, and URS Corporation. High-resolution topographic and bathymetric data along the southeastern coasts as well as historical storm data will be collected and analyzed for verification of the four academic models and the NOAA SLOSH model. After verification, the models will be used to determine how different model features or attributes will affect model accuracy and efficiency, and how model parameters and options such as grid density and time steps can be varied to optimize modeling accuracy and efficiency. The different models will be used to produce storm surge atlases (similar to the SLOSH maps) and prototype FIRMs, and these products will be compared to determine how sensitive they are to different model features and attributes. The test bed will be complete by the end of 2010. ________ SOURCE: <http://ioos.coastal.ufl.edu/>, <http://ioos.noaa.gov/>. improvement over WHAFIS. These changes, illus- Recommendation. FEMA should expand collection trated in Figure 5.6, would significantly advance of high-resolution topographic data to all coastal FEMA’s coastal models by yielding more accurate counties and require collection of post-storm topo- estimates of the SWEL, wave crest, and BFE. graphic data to validate storm surge and wave models and improve their accuracy. Recommendation. FEMA should work toward a capability to use coupled surge-wave-structure mod- Bathymetric Data els to calculate base flood elevations, starting with incorporating coupled two-dimensional surge and Accurate bathymetry is a prerequisite for accurate wave models into mapping practice. simulation of storm surge, waves, and coastal flood- ing. Since storm surge and waves propagate over a Post-storm Topographic Data long distance before landfall, it is necessary to have accurate bathymetry for both the offshore (greater than Topographic data following a 1 percent annual 20-meter depth) and the nearshore (less than 20-meter chance or more severe storm is becoming increasingly depth) regions. Currently available bathymetric data available in some coastal areas. Post-hurricane Katrina are often outdated, particularly far from shore where and Rita topographic data were used in Louisiana and the data may be decades old. However, updating Mississippi to validate the existing levee overtopping- b ­ athymetric data is costly. Given limited funding, erosion model (IPET, 2008). These data could also priority should be given to bathymetric surveys in the be used to develop and validate more robust storm nearshore region where high surge and waves develop surge and wave models in the future. Precedence for and affect coastal communities. Nonlinear wave collecting post-storm topography during most of the m ­ odels have shown that infragravity waves (waves with recent storms has been set and should become the new a period of 20 to 300 seconds) are created by wave- standard practice. bathymetry interactions at depths of 15 to 20 meters

76 MAPPING THE ZONE Probabilistic Hurricane Hurricane hurricane wind ensemble and data model return period Topographic Bathymetric data data Input data Enhanced “structure” models Storm surge Wave model model Coupled 1 percent annual chance surge-wave-“structure” BFE and wave crest model for BFE and wave crest Flood insurance FIRM rate zone Figure 5-6.eps FIGURE 5.6  Recommended coastal flood modeling and mapping procedures for FEMA. Coupled surge-wave-structure models allow calculation of 1 percent annual chance SWEL, wave setup, wave crest, and BFE simultaneously. Enhanced “structure” models account for surface roughness, erosion, and overtopping or failure of topographic features. In the interim, the committee recommends using post-storm topography and new data to develop or validate the “structure” models and to validate the CHAMP/WHAFIS erosion-wave calculations and using fully coupled surge-wave models for SWEL and wave crest calculations. and shallower. The extent to which perturbations in A Comprehensive Coastal Flood Mapping the bathymetry affect storm surges or waves modeled Uncertainty Study using FEMA’s flood mapping methods is unknown, although preliminary tests suggest that surge and FEMA has overseen many incremental improve- waves are more sensitive to nearshore bathymetry than ments to the basic CHAMP/WHAFIS model structure. to offshore bathymetry. Some of the patches contain simplifying assumptions that could increase uncertainty in the calculated BFE. Recommendation. FEMA should work with NOAA The uncertainties associated with these patches, how- and the USACE to acquire high-accuracy ­bathymetric ever, have never been assessed quantitatively. Similarly, data in coastal, estuarine, and riverine areas. the research community has been creating increasingly

COASTAL FLOODING 77 sophisticated 2-D and 3-D models for surge, waves, and over the last 30 years. The modeling changes were other coastal phenomena (e.g., Sheng and Alymov, 2002; usually incorporated in the form of patches. Modeling IPET, 2008). Whether any of these new models would methodology is now poised for a major step forward, improve FEMA’s modeling process is just beginning to enabled by the availability of more advanced models be assessed in test beds. For example, the test bed led and increased computing power, and sped by the need by the University of Florida is comparing four research to better understand and represent coastal flood pro- storm surge and inundation models as well as the flood cesses in the wake of Hurricane Katrina. maps produced using the models. A comprehensive The key to improving coastal flood maps lies in uncertainty study could help identify opportunities to improving the coastal flood models that are used to increase the accuracy of coastal flood studies and priori- calculate the BFE, improving estimates of hurricane ties for improving FEMA’s coastal flood modeling and return period, and gathering more accurate pre- and mapping methods. post-storm topographic data. Published studies com- paring WHAFIS with 2-D surge and wave models Recommendation. FEMA should commission an suggest that coupled 2-D surge and wave models yield external advisory group to conduct an independent, more accurate BFEs, and the committee endorses their comprehensive assessment of coastal flood models to use. Other models emerging from the research com­ identify ways to reduce uncertainties in the models munity offer new or enhanced capabilities—such as and to improve the accuracy of BFEs. those for calculating the effect of waves on storm surge and the effect of levees, marshes, or dunes on storm Such an assessment could consider factors such as surge and waves—but they have not been compared to one another or to FEMA models to determine whether • Performance metrics and standards for storm incorporating them into mapping practice would sig- surge models and wind fields, nificantly improve the accuracy of coastal flood maps. • The necessary size of the coastal domain for A comprehensive model intercomparison study would storm surge simulation, help focus effort on which models should be further • The effectiveness of patches applied to the developed and adopted into FEMA methodology. The WHAFIS/CHAMP model, and ultimate goal would be to use coupled models of storm • The level of uncertainty associated with ­current surge, waves, and the effects of surface roughness, ero- 2-D and 3-D models, probabilistic methods, and sion, and overtopping or failure of topographic features WHAFIS. to calculate the 1 percent annual chance stillwater ele- vation, wave setup, wave crest, and base flood elevation CONCLUSIONS simultaneously. Similarly, cost comparisons of recent coastal mapping studies in Louisiana, ­Mississippi, and Coastal flood studies rely on models of atmospheric North Carolina—which were not available at the time and ocean phenomena that originate far from shore and of writing of this report—with older studies would that change in the nearshore and onshore environment. help FEMA choose which new models are most cost- Considerable progress has been made in modeling e ­ ffective to pursue. these phenomena and mapping coastal flood hazard See <http://ioos.coastal.ufl.edu>.

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Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps portray the height and extent to which flooding is expected to occur, and they form the basis for setting flood insurance premiums and regulating development in the floodplain. As such, they are an important tool for individuals, businesses, communities, and government agencies to understand and deal with flood hazard and flood risk. Improving map accuracy is therefore not an academic question—better maps help everyone.

Making and maintaining an accurate flood map is neither simple nor inexpensive. Even after an investment of more than $1 billion to take flood maps into the digital world, only 21 percent of the population has maps that meet or exceed national flood hazard data quality thresholds. Even when floodplains are mapped with high accuracy, land development and natural changes to the landscape or hydrologic systems create the need for continuous map maintenance and updates.

Mapping the Zone examines the factors that affect flood map accuracy, assesses the benefits and costs of more accurate flood maps, and recommends ways to improve flood mapping, communication, and management of flood-related data.

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